tFileInputPositional MapReduce properties

Positional

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Talend Documentation Team
EnrichVersion
6.4
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Talend Data Management Platform
Talend Big Data
Talend MDM Platform
Talend Real-Time Big Data Platform
Talend Open Studio for MDM
Talend Data Integration
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Talend Data Fabric
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Talend ESB
Talend Open Studio for Data Integration
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Data Quality and Preparation > Third-party systems > File components (Integration) > Positional components
Data Governance > Third-party systems > File components (Integration) > Positional components
Design and Development > Third-party systems > File components (Integration) > Positional components
EnrichPlatform
Talend Studio

These properties are used to configure tFileInputPositional running in the MapReduce Job framework.

The MapReduce tFileInputPositional component belongs to the MapReduce family.

The component in this framework is available in all subscription-based Talend products with Big Data and Talend Data Fabric.

Basic settings

Property type

Either Built-In or Repository.

 

Built-In: No property data stored centrally.

 

Repository: Select the repository file where the properties are stored.

The properties are stored centrally under the Hadoop Cluster node of the Repository tree.

The fields that come after are pre-filled in using the fetched data.

For further information about the Hadoop Cluster node, see the Getting Started Guide.

Schema and Edit Schema

A schema is a row description. It defines the number of fields (columns) to be processed and passed on to the next component. The schema is either Built-In or stored remotely in the Repository.

Click Edit schema to make changes to the schema. Note that if you make changes, the schema automatically becomes built-in.

 

Built-In: You create and store the schema locally for this component only. Related topic: see Talend Studio User Guide.

 

Repository: You have already created the schema and stored it in the Repository. You can reuse it in various projects and Job designs. Related topic: see Talend Studio User Guide.

Folder/File

Browse to, or enter the path pointing to the data to be used in the file system.

If the path you set points to a folder, this component will read all of the files stored in that folder, for example,/user/talend/in; if sub-folders exist, the sub-folders are automatically ignored unless you define the property mapreduce.input.fileinputformat.input.dir.recursive to be true in the Hadoop properties table in the Hadoop configuration tab.

If you want to specify more than one files or directories in this field, separate each path using a comma (,).

If the file to be read is a compressed one, enter the file name with its extension; then tFileInputPositional automatically decompresses it at runtime. The supported compression formats and their corresponding extensions are:

  • DEFLATE: *.deflate

  • gzip: *.gz

  • bzip2: *.bz2

  • LZO: *.lzo

Note that you need to ensure you have properly configured the connection to the Hadoop distribution to be used in the Hadoop configuration tab in the Run view.

Die on error

Select this check box to stop the execution of the Job when an error occurs.

Clear the check box to skip any rows on error and complete the process for error-free rows. When errors are skipped, you can collect the rows on error using a Row > Reject link.

Row separator

Enter the separator used to identify the end of a row.

Customize

Select this check box to customize the data format of the positional file and define the table columns:

Column: Select the column you want to customize.

Size: Enter the column size.

Padding char: Enter, between double quotation marks, the padding charater you need to remove from the field. A space by default.

Alignment: Select the appropriate alignment parameter.

Pattern

Enter between double quotes the length values separated by commas, interpreted as a string. Make sure the values entered in this field are consistent with the schema defined.

Header

Enter the number of rows to be skipped in the beginning of file.

For example, enter 0 to ignore no rows for the data without header and set 1 for the data with header at the first row.

Skip empty rows

Select this check box to skip the empty rows.

Advanced settings

Custom Encoding

You may encounter encoding issues when you process the stored data. In that situation, select this check box to display the Encoding list.

Then select the encoding to be used from the list or select Custom and define it manually.

Advanced separator (for number)

Select this check box to change the separator used for numbers. By default, the thousands separator is a comma (,) and the decimal separator is a period (.).

Trim columns

Select this check box to remove the leading and trailing whitespaces from all columns. When this check box is cleared, the Check column to trim table is displayed, which lets you select particular columns to trim.

Global Variables

Global Variables

ERROR_MESSAGE: the error message generated by the component when an error occurs. This is an After variable and it returns a string. This variable functions only if the Die on error check box is cleared, if the component has this check box.

A Flow variable functions during the execution of a component while an After variable functions after the execution of the component.

To fill up a field or expression with a variable, press Ctrl + Space to access the variable list and choose the variable to use from it.

For further information about variables, see Talend Studio User Guide.

Usage

Usage rule

In a Talend Map/Reduce Job, it is used as a start component and requires a transformation component as output link. The other components used along with it must be Map/Reduce components, too. They generate native Map/Reduce code that can be executed directly in Hadoop.

Once a Map/Reduce Job is opened in the workspace, tFileInputDelimited as well as the MapReduce family appears in the Palette of the Studio.

Note that in this documentation, unless otherwise explicitly stated, a scenario presents only Standard Jobs, that is to say traditional Talend data integration Jobs, and non Map/Reduce Jobs.

Hadoop Connection

You need to use the Hadoop Configuration tab in the Run view to define the connection to a given Hadoop distribution for the whole Job.

This connection is effective on a per-Job basis.